@betterdb/mcp

Give your AI assistant deep visibility into your Valkey and Redis databases. The BetterDB MCP server connects Claude Code, Cursor, Windsurf, and other MCP-compatible clients to the BetterDB monitoring platform — letting your AI query real-time metrics, diagnose slow commands, detect anomalies, and investigate incidents without leaving your editor.

BetterDB Monitor gives you live dashboards for the AI workloads running on your Valkey:

• AI Cache & Memory - hit rate, cost saved, evictions, and index size across all your caches and memory stores, with history.
• AI Traces - OpenTelemetry waterfalls for each request, correlated with live Valkey state to explain every cache hit and miss.

Run it self-hosted (docker run -p 3001:3001 betterdb/monitor), or use BetterDB Cloud - which can also provision a managed, TLS-enabled Valkey instance (Search module included) in one click.

BetterDB is a monitoring and observability platform built for Valkey and Redis providing real-time dashboards, anomaly detection, and operational intelligence for your Valkey and Redis deployments. Unlike tools that only show a live snapshot, BetterDB persists historical metrics, slowlogs, and audit trails — so you can investigate what happened yesterday, not just what's happening now.

Key capabilities exposed through MCP:

• Real-time health checks — memory fragmentation, hit rate, replication lag, connected clients
• Slow command analysis — slowlog and COMMANDLOG (Valkey 8+) with pattern aggregation
• Hot key detection — find cache-busting keys via LFU frequency scores or idle time analysis
• Cluster-wide visibility — per-node stats, aggregated slowlogs, and slot-level metrics across all nodes
• Anomaly detection — Z-score analysis on memory, CPU, hit rate, and other metrics (Pro)
• Client activity tracking — connection counts, command distribution, and buffer usage over time
• ACL audit log — investigate auth failures and access patterns
• Latency event history — track latency trends for specific event types

In BetterDB, go to Settings → MCP Tokens and generate a new token.

Add to your MCP client config (e.g. Claude Code or OpenAI Codex):

{
  "mcpServers": {
    "betterdb": {
      "type": "stdio",
      "command": "npx",
      "args": ["@betterdb/mcp"],
      "env": {
        "BETTERDB_URL": "https://<your-workspace>.app.betterdb.com",
        "BETTERDB_TOKEN": "<your-token>"
      }
    }
  }
}

For local development with an existing monitor (token not required):

{
  "mcpServers": {
    "betterdb": {
      "type": "stdio",
      "command": "npx",
      "args": ["@betterdb/mcp"],
      "env": {
        "BETTERDB_URL": "http://localhost:3001"
      }
    }
  }
}

For zero-config local development (auto-starts and manages a monitor process):

{
  "mcpServers": {
    "betterdb": {
      "type": "stdio",
      "command": "npx",
      "args": ["@betterdb/mcp", "--autostart", "--persist"]
    }
  }
}

Once connected, your AI assistant can query your databases directly:

• "What's the health of my production Valkey instance?"
• "Show me the slowest commands from the last hour"
• "Are there any hot keys causing uneven load?"
• "Which cluster node has the highest memory usage?"
• "Have there been any anomalies in the last 24 hours?"
• "Tune the threshold on my faq-cache — propose a change for me to review"
• "Why is the weather_lookup tool's hit rate so low?"

For deployments running the Search module (valkey-search / RediSearch).

For AI components (semantic caches, agent caches, agent-memory stores, retrieval pipelines) and traces ingested via OpenTelemetry.

For deployments running @betterdb/semantic-cache or @betterdb/agent-cache. Caches register themselves in a Valkey-side discovery hash; Monitor exposes them through the tools below.

Read-only:

Propose changes (advisory — no Valkey writes until approved):

Approve / reject / list:

• Node.js 20+
• A running BetterDB instance (cloud or self-hosted), or use --autostart to have the MCP server manage one automatically

Full docs: docs.betterdb.com

See LICENSE for details.